Official platform of Tsinghua Big Data Research Center, sharing the team's latest research, teaching updates, and big data news.
This guide walks you through a clean removal of OpenClaw—including resetting configurations, running the official uninstall command with appropriate flags, deleting the CLI tool across package managers, and handling leftover API keys—so you can safely retire the software on Windows, macOS, or WSL environments.
The scLong foundation model, trained on 48 million cells and 28 k genes, integrates full‑gene expression with Gene Ontology knowledge to outperform existing methods on genetic perturbation, chemical response, cancer drug prediction, gene‑regulatory network inference, and batch integration tasks.
The article explains that expanding LLM context windows leads to attention dilution and retrieval collapse, degrading answer quality, and argues that Retrieval‑Augmented Generation remains essential because it preserves signal density through focused retrieval and selective prompting.
This guide walks you through the essential steps to transform a freshly installed OpenClaw instance into a stable, production‑ready AI assistant, covering troubleshooting, configuration files, memory persistence, model selection, security hardening, Telegram integration, browser setup, and automated heartbeat and cron management.
This article traces the century‑long journey of dancing robots—from early mechanical automata and electric toys to modern AI‑driven performers—detailing hardware upgrades, control‑system breakthroughs, perception technologies, and future application scenarios that turn stage spectacles into everyday utilities.
OpenMAIC, the world’s first multi‑agent generative learning framework released by Tsinghua University, transforms technical documents into zero‑barrier interactive courses, supports AI‑driven lesson planning, multi‑agent discussions, and plug‑in extensions, and is rapidly evolving through 2024‑2026 to reshape education and beyond.
This tutorial explains how to automatically locate trend change points in large collections of time series by combining grid search with piecewise regression, covering the underlying theory, cost functions, implementation in R and Python, and practical constraints to avoid over‑fitting.
The article explains three practical prompting techniques—periodic core requirement restatement, repeated inclusion of the original text, and multiple task repetitions—that help large language models maintain focus, avoid missing details, and produce deeper, more accurate outputs in long‑context and multi‑rule scenarios, with concrete examples.
UniScientist, a 30‑billion‑parameter open‑source model from UniPat AI, demonstrates a closed‑loop scientific research workflow—generating hypotheses, gathering evidence, performing reproducible derivations, and iteratively refining conclusions—while achieving benchmark scores comparable to much larger proprietary systems across multiple scientific evaluation suites.
This article introduces the open-source AI companion AIRI—an open-source replica of the popular virtual streamer Neuro-sama—explains its features such as self-hosting, multi-model support, game integration, and provides step-by-step instructions for setting up the development environment, installing dependencies, and launching the web or desktop version.
